Evidence map›Paper›PMID 41667768›Full record

ArticleScientific reports2026

Identifying the shared genes and their related microRNAs, metabolites, and pathways in ischemic stroke and epilepsy.

Yu Chen, Shuhong Man, Qinfeng Li, Yuelong Ji, Biwen Peng, Yansheng Ding, Jian Xu

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In one paragraph

Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Yu Chen *Department of Clinical Laboratory, Weifang Maternal and Child Health Hospital, No. 12007, Yingqian Street, High-tech Zone, Weifang, 261011, Shandong, China.
Shuhong Man *Department of Obstetrics and Gynecology, Weifang People's Hospital, Weifang, 261000, Shandong, China.
Qinfeng LiDepartment of Clinical Laboratory, Weifang Maternal and Child Health Hospital, No. 12007, Yingqian Street, High-tech Zone, Weifang, 261011, Shandong, China.
Yuelong JiSchool of Public Health, Peking University, Beijing, 100191, China.
Biwen PengDepartment of Physiology, School of Basic Medical Sciences, Wuhan University, Wuhan, 430071, China. pengbiwen@whu.edu.cn.
Yansheng DingDepartment of Clinical Laboratory, Weifang Maternal and Child Health Hospital, No. 12007, Yingqian Street, High-tech Zone, Weifang, 261011, Shandong, China. 1548895227@qq.com.
Jian XuDepartment of Clinical Laboratory, Weifang Maternal and Child Health Hospital, No. 12007, Yingqian Street, High-tech Zone, Weifang, 261011, Shandong, China. ydukongjian@163.com.ORCID http://orcid.org/0000-0002-3087-824X

Funding

China Postdoctoral Science Foundation 2018M642618National Natural Science Foundation of China 81401230Natural Science Foundation of Shandong Province ZR2019BH056Shandong Provincial Medical and Health Science and Technology Project 202411001099
6 · The paper itself

Abstract

Background This study aimed to identify shared genes between ischemic stroke (IS) and epilepsy and explore underlying mechanisms. Methods Transcriptomic datasets from the GEO database were analyzed using differential expression and weighted gene co-expression network analysis (WGCNA). Hub-shared genes were identified through protein-protein interaction networks, ROC analysis, and expression validation. Upstream miRNAs were predicted. Additionally, untargeted plasma metabolomics was performed on children with epilepsy and healthy controls, followed by differential metabolite analysis and metabolic pathway construction. Results WGCNA revealed 594 epilepsy-related and 2,623 IS-related DEGs, with 38 shared DEGs identified, including IL10RA, CD2, and C3AR1. These genes showed high diagnostic value, with their AUC value > 0.66 in both training and validation datasets. Additionally, hsa-let-7b-5p was predicted to target C3AR1. Metabolomics identified 139 differential metabolites, and C3AR1 was implicated in synaptic vesicle cycle, taste transduction, and nicotine addiction pathways via acetylcholine. Conclusions The shared genes, especially C3AR1 may be a key regulator in the development IS and epilepsy, showing potential as a biomarker for both diseases. However, its diagnostic efficacy requires further clinical validation. Given the complexity of these diseases, future research may focus on identifying a panel of biomarkers rather than relying on a single gene.

Indexed as

EpilepsyIschemic StrokeMicroRNAsBiomarkersGene Expression ProfilingGene Regulatory NetworksHumansMetabolic Networks and PathwaysMetabolomicsProtein Interaction MapsTranscriptomeBiomarkersMicroRNAsEpilepsyIschemic strokeMetabolitesMicroRNAShared genes

Identifiers

PMID41667768
PMCPMC12963536

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